{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:J2376PDITAZBIR277E76PEGPES","short_pith_number":"pith:J2376PDI","canonical_record":{"source":{"id":"2606.21819","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-20T01:05:44Z","cross_cats_sorted":[],"title_canon_sha256":"40423b907e77d67f6ca387a8fd2b106e0f767e24a3cc3d3f38ea9de34c89febc","abstract_canon_sha256":"3d96eecd13852ed5f52eee0bdae1ffbea43345f220145a03f75b7e614859fd9c"},"schema_version":"1.0"},"canonical_sha256":"4eb7ff3c68983214475ff93fe790cf249d3a4ebd92dc3fed9fd15d04d063aabc","source":{"kind":"arxiv","id":"2606.21819","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.21819","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2606.21819v1","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.21819","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"J2376PDITAZB","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"J2376PDITAZBIR27","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"J2376PDI","created_at":"2026-06-23T01:13:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:J2376PDITAZBIR277E76PEGPES","target":"record","payload":{"canonical_record":{"source":{"id":"2606.21819","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-20T01:05:44Z","cross_cats_sorted":[],"title_canon_sha256":"40423b907e77d67f6ca387a8fd2b106e0f767e24a3cc3d3f38ea9de34c89febc","abstract_canon_sha256":"3d96eecd13852ed5f52eee0bdae1ffbea43345f220145a03f75b7e614859fd9c"},"schema_version":"1.0"},"canonical_sha256":"4eb7ff3c68983214475ff93fe790cf249d3a4ebd92dc3fed9fd15d04d063aabc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T01:13:23.651807Z","signature_b64":"lnsuxbg2PfvX0AcDtggMNOhlWGzhR6OF6K1MYJmwtfLL3g8g68A1LpTHAOSkr7DvbjQuprmq0XSfC32BXystCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4eb7ff3c68983214475ff93fe790cf249d3a4ebd92dc3fed9fd15d04d063aabc","last_reissued_at":"2026-06-23T01:13:23.651289Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T01:13:23.651289Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.21819","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T01:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vYLkurvnZsYkeJz/+Qemye5c5rWVlgNoqwY9DP+UluYtKbnGa3TI1bWcZ6pNJ2ylBM4JnZ6RJGg6njKSQolADg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T20:01:27.489490Z"},"content_sha256":"21ae104a39411c54bf329726e666ef9cde40333bfaf9ac96a6dd270b9039275f","schema_version":"1.0","event_id":"sha256:21ae104a39411c54bf329726e666ef9cde40333bfaf9ac96a6dd270b9039275f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:J2376PDITAZBIR277E76PEGPES","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Li, Kaili Zhang, Lei Zou, Wenjing Gong, Xinyue Ye, Yifan Yang, Zhengzhong Tu, Zongrong Li","submitted_at":"2026-06-20T01:05:44Z","abstract_excerpt":"Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to disaster damage assessment. Existing methods, largely based on supervised learning and task-specific fine-tuning, struggle to generalize under domain shifts, long-tailed data distributions, and heterogeneous geospatial data sources, especially in disaster scenarios. They also often lack the ability to integrate and reason across multimodal geospatial information, such as satellite images and street-view images. In this paper, we introduce RAPI"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.21819","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.21819/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T01:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XtT5S3hAN5K0gpMH/eX3/TfOZQzBknNyLnUs6eLdBvxYOic09PxXoz6Rel4B5eI/IEOE6xFExt2HnEOtfJjpAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T20:01:27.489873Z"},"content_sha256":"394db83517067a0a52e45d6047cae5e851bbeb8b760d5bc9d8f41d7c46705b03","schema_version":"1.0","event_id":"sha256:394db83517067a0a52e45d6047cae5e851bbeb8b760d5bc9d8f41d7c46705b03"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J2376PDITAZBIR277E76PEGPES/bundle.json","state_url":"https://pith.science/pith/J2376PDITAZBIR277E76PEGPES/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J2376PDITAZBIR277E76PEGPES/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-25T20:01:27Z","links":{"resolver":"https://pith.science/pith/J2376PDITAZBIR277E76PEGPES","bundle":"https://pith.science/pith/J2376PDITAZBIR277E76PEGPES/bundle.json","state":"https://pith.science/pith/J2376PDITAZBIR277E76PEGPES/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J2376PDITAZBIR277E76PEGPES/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:J2376PDITAZBIR277E76PEGPES","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3d96eecd13852ed5f52eee0bdae1ffbea43345f220145a03f75b7e614859fd9c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-20T01:05:44Z","title_canon_sha256":"40423b907e77d67f6ca387a8fd2b106e0f767e24a3cc3d3f38ea9de34c89febc"},"schema_version":"1.0","source":{"id":"2606.21819","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.21819","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2606.21819v1","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.21819","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"J2376PDITAZB","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"J2376PDITAZBIR27","created_at":"2026-06-23T01:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"J2376PDI","created_at":"2026-06-23T01:13:23Z"}],"graph_snapshots":[{"event_id":"sha256:394db83517067a0a52e45d6047cae5e851bbeb8b760d5bc9d8f41d7c46705b03","target":"graph","created_at":"2026-06-23T01:13:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.21819/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to disaster damage assessment. Existing methods, largely based on supervised learning and task-specific fine-tuning, struggle to generalize under domain shifts, long-tailed data distributions, and heterogeneous geospatial data sources, especially in disaster scenarios. They also often lack the ability to integrate and reason across multimodal geospatial information, such as satellite images and street-view images. In this paper, we introduce RAPI","authors_text":"Hao Li, Kaili Zhang, Lei Zou, Wenjing Gong, Xinyue Ye, Yifan Yang, Zhengzhong Tu, Zongrong Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-20T01:05:44Z","title":"RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.21819","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:21ae104a39411c54bf329726e666ef9cde40333bfaf9ac96a6dd270b9039275f","target":"record","created_at":"2026-06-23T01:13:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3d96eecd13852ed5f52eee0bdae1ffbea43345f220145a03f75b7e614859fd9c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-20T01:05:44Z","title_canon_sha256":"40423b907e77d67f6ca387a8fd2b106e0f767e24a3cc3d3f38ea9de34c89febc"},"schema_version":"1.0","source":{"id":"2606.21819","kind":"arxiv","version":1}},"canonical_sha256":"4eb7ff3c68983214475ff93fe790cf249d3a4ebd92dc3fed9fd15d04d063aabc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4eb7ff3c68983214475ff93fe790cf249d3a4ebd92dc3fed9fd15d04d063aabc","first_computed_at":"2026-06-23T01:13:23.651289Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T01:13:23.651289Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lnsuxbg2PfvX0AcDtggMNOhlWGzhR6OF6K1MYJmwtfLL3g8g68A1LpTHAOSkr7DvbjQuprmq0XSfC32BXystCA==","signature_status":"signed_v1","signed_at":"2026-06-23T01:13:23.651807Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.21819","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:21ae104a39411c54bf329726e666ef9cde40333bfaf9ac96a6dd270b9039275f","sha256:394db83517067a0a52e45d6047cae5e851bbeb8b760d5bc9d8f41d7c46705b03"],"state_sha256":"13de34b487556bfbbedfd86e400bea9b191ca981910ed33bbc8065b53bd3f9af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"plX52q7HEARdryfALxJkGU2J4iuhHkuXyoKcpT2g8Es8a1XQIJ2kzsQze9RsV9milbsqqA3B10H7mJF3X8GECg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T20:01:27.491962Z","bundle_sha256":"e7457b7dea1b6ba8567b61b3efd1a1c4934d4c7090498f5f36eaaf947ac261f8"}}